A federated probabilistic environment typically comprises a collection of networked, interoperable hubs, each of which can comprise computer systems, databases, and/or other resources. A federated probabilistic search refers to an informational retrieval technology where a user can make a single query request to an originating hub, which in turn distributes the query request to other hubs in the federated probabilistic environment. Data retrieved from a federated probabilistic search can be consolidated by the originating hub and returned to the user.
Each hub in a federated probabilistic search environment typically uses confidence scores to rank the relevance of search results to the search query. A high confidence score indicates a strong likelihood of relevance to the search query. Confidence score thresholds can be used to determine whether a particular search result will be included in the results returned to a user based on the confidence score associated with that result. For example, a confidence score greater than or equal to a confidence score threshold may be included in the results returned to a user. Each hub in a federated probabilistic search environment can be configured differently with different algorithms and thresholds.